5 Ways Artificial Intelligence Transform Invoice Data Capture
For some, the thought of artificial intelligence brings with it visions of self-driving vehicles, robot doctors, or automated concierge services. Artificial intelligence in invoice data capture may not be science fiction film material, but the impact certainly has been transformative. Data capture solutions with artificial intelligence offer the accounts payable departments that adopt the technology great rewards. Above all, it helps eliminate the repetitive, menial manual tasks that have painted the profession as a tactical back-office function.
Sure, the idea of machines performing invoice data capture may concern some. Fortunately, the Institute of Finance and Management’s (IOFM) “2018 Future of Accounts Payable Study” found encouraging results. For instance, the accounts payable practitioners who were surveyed consider artificial intelligence critical. Specifically, they ranked it among the most important technologies in the next three years in their profession. This white paper provides a definition of artificial intelligence, details what finance departments want from the technology, describes how artificial intelligence works in data capture, and shows five transformative benefits the technology delivers to the invoice data capture process.
What is Artificial Intelligence?
Artificial intelligence enables software or machines to understand task by producing for itself the rules programmers cannot specify. Above all, artificial intelligence was developed for:
- Automating repetitive tasks
- Analyzing large amounts of data
- Identifying certain features in data
- Applying these features to new data
By analyzing data sets and patterns, artificial intelligence automates menial, time-consuming tasks such as invoice data capture and the matching of invoices to purchase orders and/or proof-of-delivery documents. In short, the technology understands the tasks that must be performed for a business application.
Artificial intelligence also can mine information to provide contextual insights for decision-making and financial planning. For instance, the technology enables organizations to intelligently leverage data from millions of transactions stored in repositories or other systems to find invoice information.
What’s more, artificial intelligence employs so-called machine learning to achieve better results over time. Machine learning uses sophisticated algorithms to eliminate the complex, rigid and time-consuming process of programming all the steps required to automate a business process such as invoice data capture. The technology can “train” itself to recognize documents (e.g. invoices) and to capture the necessary data based on their characteristics (such as extracting the invoice amount).